Why should we know this?

Not watching that video for a number of reasons, namely that ten seconds in they hadn’t said anything of substance, their first claim was incorrect (Amazon does not prohibit use of gen ai in books, nor do they require its use be disclosed to the public, no matter how much you might wish it did), and there was nothing in the description of substance, which in instances like this generally means the video will largely be devoid of substance.

What books is the Math Sorcerer selling? Are they the ones on Amazon linked from their page? Are they selling all of those or just promoting most of them?

Why do we think they were generated with AI?

When you say “generated with AI,” what do you mean?

• Generated entirely with AI, without even editing? Then why do they have so many 5 star reviews?
• Generated with AI and then heavily edited?
• Written partly by hand with some pieces written by unedited GenAI?
• Written partly by hand with some pieces written by edited GenAI?
• AI was used for ideation?
• AI was used during editing? E.g., Grammarly?
• GenAI was used during editing?E.g., “ChatGPT, review this chapter and give me any feedback. If sections need rewritten go ahead and take a first pass.”
• AI might have been used, but we don’t know for sure, and the issue is that some passages just “read like AI?”

And what’s the result? Are the books misleading in some way? That’s the most legitimate actual concern I can think of (I’m sure the people screaming that AI isn’t fair use would disagree, but if that’s the concern, settle it in court).

Look up “LLM quantization.” The idea is that each parameter is a number; by default they use 16 bits of precision, but if you scale them into smaller sizes, you use less space and have less precision, but you still have the same parameters. There’s not much quality loss going from 16 bits to 8, but it gets more noticeable as you get lower and lower. (That said, there’s are ternary bit models being trained from scratch that use 1.58 bits per parameter and are allegedly just as good as fp16 models of the same parameter count.)

If you’re using a 4-bit quantization, then you need about half that number in VRAM. Q4_K_M is better than Q4, but also a bit larger. Ollama generally defaults to Q4_K_M. If you can handle a higher quantization, Q6_K is generally best. If you can’t quite fit it, Q5_K_M is generally better than any other option, followed by Q5_K_S.

For example, Llama3.3 70B, which has 70.6 billion parameters, has the following sizes for some of its quantizations:

• q4_K_M (the default): 43 GB
• fp16: 141 GB
• q8: 75 GB
• q6_K: 58 GB
• q5_k_m: 50 GB
• q4: 40 GB
• q3_K_M: 34 GB
• q2_K: 26 GB

This is why I run a lot of Q4_K_M 70B models on two 3090s.

Generally speaking, there’s not a perceptible quality drop going to Q6_K from 8 bit quantization (though I have heard this is less true with MoE models). Below Q6, there’s a bit of a drop between it and 5 and then 4, but the model’s still decent. Below 4-bit quantizations you can generally get better results from a smaller parameter model at a higher quantization.

TheBloke on Huggingface has a lot of GGUF quantization repos, and most, if not all of them, have a blurb about the different quantization types and which are recommended. When Ollama.com doesn’t have a model I want, I’m generally able to find one there.

I recommend a used 3090, as that has 24 GB of VRAM and generally can be found for $800ish or less (at least when I last checked, in February). It’s much cheaper than a 4090 and while admittedly more expensive than the inexpensive 24GB Nvidia Tesla card (the P40?) it also has much better performance and CUDA support.

I have dual 3090s so my performance won’t translate directly to what a single GPU would get, but it’s pretty easy to find stats on 3090 performance.

The above post says it has support for Ollama, so I don’t think this is the case… but the instructions in the Readme do make it seem like it’s dependent on OpenAI.

16 GB of RAM, though? Is it even optimized for the Ryzen 9950X3D?

And a 4 TB SSD - not even necessarily NVME?

Doesn’t seem high powered to me.

Are you saying that NAT isn’t effectively a firewall or that a NAT firewall isn’t effectively a firewall?

Is there a way to use symlinks instead? I’d think it would be possible, even with Docker - it would just require the torrent directory to be mounted read-only in the same location in every Docker container that had symlinks to files on it.

Depending on setup this can be true with Jellyfin, too. I have a domain registered, use dynamic DNS, and have Traefik direct a subdomain to my Jellyfin server. My mobile clients are configured using that. My local clients use the local static IP.

If my internet goes down, my mobile clients can’t connect, even on the LAN.

On the other hand it is a conduit for censorship. If an admin doesn’t like what you post on another instance, then they can censor you everywhere.

Such a user can

• Create an account on a different instance
• Spin up their own instance

Do you mean like a FOSS version of https://soundiiz.com/transfer-playlist-and-favorites?

Or at a song/album level, a FOSS version of https://odesli.co/?

Under notes, where you said my name, did you mean “Hedgedoc?”

local docker hub proxy

Do you mean a Docker container registry? If so, here are a couple options:

• Use the official Docker registry: https://www.docker.com/blog/how-to-use-your-own-registry-2/
• Self-host forgejo or gitea and use the included package registry, which is automatically enabled. Details: https://forgejo.org/docs/latest/user/packages/

Oh 100% agreed - in this instance, it’s clear that OBS has a well maintained package that should be prioritized. But they could keep their repo first and remove OBS (and other known-to-be-well-maintained apps) from it to accomplish that.

They put their repo first on the list.

Right. And are we talking about the list for OBS or of repos in general? I doubt Fedora sets the priority on a package level. And if they don’t, and if there are some other packages in Flathub that are problematic, then it makes sense to prioritize their own repo over them.

That said, if those problematic packages come from other repositories, or if not but there’s another alternative to putting their repo first that would have prevented unofficial builds from showing up first, but wouldn’t have deprioritized official, verified ones like OBS, then it’s a different story. I haven’t maintained a package on Flathub like the original commenter you replied to but I don’t get the impression that that’s the case.

Why did Fedora make their packages take priority? Is it because the priority is otherwise random and if you don’t have a priority set, that leads to the issue they mentioned? Because if so, that sounds like a reasonable action by Fedora and like the real culprit is Flathub.

You cannot encrypt email End to End.

Incorrect.

https://support.mozilla.org/en-US/kb/introduction-to-e2e-encryption

It has to be stored in plaintext somewhere.

1. It doesn’t.
2. Even if it did, that wouldn’t mean it wasn’t E2EE.

Yahoo does not offer encrypted email.

It doesn’t need to. https://support.mozilla.org/en-US/kb/thunderbird-and-yahoo

I can’t use signal.

Why? Do you not have a phone number? Is it blocked in your country? Are you legally prohibited from using software with end to end encryption?

There’s no need to bond with your own child?

Giphy has a documented API that you could use. There have been bulk downloaders, but I didn’t see any that had recent activity. However you still might be able to use one to model your own script after, like https://github.com/jcpsimmons/giphy-stacks

There were downloaders for Gfycat - gallery-dl supported it at one point - but it’s down now. However you might be able to find collections that other people downloaded and are now hosting. You could also use the Internet Archive - they have tools and APIs documented

There’s a Tenor mass downloader that uses the Tenor API and an API key that you provide.

Imgur has GIFs is supported by gallery-dl, so that’s an option.

Also, read over https://github.com/simon987/awesome-datahoarding - there may be something useful for you there.

In terms of hosting, it would depend on my user base and if I want users to be able to upload GIFs, too. If it was just my close friends, then Immich would probably be fine, but if we had people I didn’t know directly using it, I’d want a more refined solution.

There’s Gifable, which is pretty focused, but looks like it has a pretty small following. I haven’t used it myself to see how suitable it is. If you self-host it (or something else that uses S3), note that you can use MinIO or LocalStack for the S3 container rather than using AWS directly. I’m using MinIO as part of my stack now, though for a completely different app.

MediaCMS is another option. Less focused on GIFs but more actively developed, and intended to be used for this sort of purpose.

No. Trickle down economics refers to things that benefit the wealthy (mostly government policies, particularly related to taxes and subsidies) that will allegedly benefit everyone by “trickling down.” Supply-side economics are an example of trickle-down economics. Trickle-down economic policies have been shown to effectively increase income inequality and studies suggest a link between them and reduced overall growth.

Giving the wealthy tax breaks in the hopes that they’ll spend the extra money they have available on security details, on the other hand, would be an example of trickle down economics.